From Desk to Field: From Desk to Field: Semiotic Research via Qualitative Semiotic Research via Qualitative and Quantitative Methods and Quantitative Methods Early-Fall School of Semiotics “ “ Ways of Semiotic Research Ways of Semiotic Research ” ” Sept. 10 / 2015, Sozopol / Bulgaria Dr. Dimitar Trendafilov New Bulgarian University – Sofia South-East European Center for Semiotic Studies / Dep. of Economics
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From Desk to Field: From Desk to Field:
Semiotic Research via Qualitative Semiotic Research via Qualitative
and Quantitative Methodsand Quantitative Methods
Early-Fall School of Semiotics
““Ways of Semiotic ResearchWays of Semiotic Research””
Sept. 10 / 2015, Sozopol
/ Bulgaria
Dr. Dimitar TrendafilovNew Bulgarian University – Sofia
South-East European Center for Semiotic Studies / Dep. of Economics
Agenda
Meaning
Why Qual. & Quant. methods?
Triangulation Argument
Secondary Data Analysis
Ethnography and Netnography
The Semantic Differential
Meaning?
First and foremost, we need to know a little bit more about Meaning and its crucial place in our lives, even in our everyday routine. Actually, it’s the key tool for us to share our experience, impressions, ideas and even feelings, and to provide coordination of our acts and goals. And all this happens despite in almost all of its manifestations meaning is affected by dilution, improvement or extension.
That’s why semiotics distinguishes denotation and connotation, basis and uses of meaning, that could stay amazingly far from one another. Meaning is a living and highly changeable entity, which is related with so many factors that it’s impossible to any individual to keep it as it is. But, however, we keep trying to grasp it for different purposes. In the context of EFSS 2015, our purpose is just to use it as a working term to present some research approaches.
Meaning and Culture – from language to cultural symbols (L. Oswald [2015: 140-141] – Whorf’s Hypothesis about the French distinction between raw and cooked lamb, including distinguishing various parts of the animal, while in the UK it refers predominantly to wool and textile industry).
Why Qual. and Quant. Methods
together?
A lot of factors cause the urban legend that Qual. and
Quant. methods are in some kind of opposition while, in
fact, they are/could be highly complementary.
Just to name a few factors: the artificial division
between them in universities and in research agencies,
the specialization researchers usually have, the
technical training and availability they need, etc.
Qual. and Quant. Methods together /1
Quantitative methods are focused on “How
many/much?”, but they need very clear idea what to
measure and how questionnaire to be designed.
Qualitative methods aim to find answer/s of the
question “Why?”, but it takes time and needs both right
questions to be asked, to the right people, and an
verification by broader sample.
Qual. and Quant. Methods together /2
According to the Phase-model Qual. methods generate hypotheses and Quant. test them (Kelle and Erzberger 2004).
However, it’s possible for Qual. procedures to help in filling gaps in explanation using “sociological variables”where statistical relations are explained by additional assumptions after the event, while Quant. procedures are able to show super-individual structural relationships, which are not consciously observed by the individuals and don’t come out by the interviews.
Qual. and Quant. Methods together /3
The usual accusation to semiotics is the subjectivity, the high level of personal intervention it has. This means that the results depend on the experience, involvement and skills of the researcher beyond the level practitioners can endorse. That’s why semiotics meets limited acceptance among professional research methods, especially when we are talking about the business area.
Business prefers the language of numbers in order to be able to compare and to conglomerate data. What business forgets very often, however, is the fact that the beginning and in the end of the process stays some human being who designs the research instruments and eventually interprets the raw data to convert it in useful information. The device that processes the numbers is important, but it reminds to be an instrument, not different than spade or fork.
According to the phenomenon studied it’s challenging to
find the best/relevant oppositions about it since they are
not self-evident (for example, in everyday speech in BG,
cars are never “fast - slow”, but “powerful - tied”).
It’s better not to put antonyms constructed by negation
(like “clear - unclear”, rather “clear - vague”) because it
causes negative attitude instead of evaluation and rating.
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